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Record W2472573627 · doi:10.1093/mnras/stw1486

Radio variability in the Phoenix Deep Survey at 1.4 GHz

2016· article· en· W2472573627 on OpenAlexaff
P. J. Hancock, Jason Drury, M. E. Bell, Tara Murphy, B. M. Gaensler

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsPhysicsPhoenixAstrophysicsPopulationVariable (mathematics)AstronomyGeographyDemography

Abstract

fetched live from OpenAlex

We use archival data from the Phoenix Deep Survey to investigate the variable radio source population above 1 mJy beam−1 at 1.4 GHz. Given the similarity of this survey to other such surveys we take the opportunity to investigate the conflicting results which have appeared in the literature. Two previous surveys for variability conducted with the Very Large Array (VLA) achieved a sensitivity of 1 mJy beam−1. However, one survey found an areal density of radio variables on time-scales of decades that is a factor of ∼4 times greater than a second survey which was conducted on time-scales of less than a few years. In the Phoenix deep field we measure the density of variable radio sources to be ρ = 0.98 deg−2 on time-scales of 6 months to 8 yr. We make use of Wide-field Infrared Survey Explorer infrared cross-ids, and identify all variable sources as an active galactic nucleus of some description. We suggest that the discrepancy between previous VLA results is due to the different time-scales probed by each of the surveys, and that radio variability at 1.4 GHz is greatest on time-scales of 2–5 yr.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.198
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2016
Admission routes1
Has abstractyes

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